Collaborative filtering and A/B testing are popular marketing testing techniques designed to test the impact of a product on users. Collaborative filtering involves making predictions about a user's interests based on preference information collected from many users with similar interests. In collaborative filtering, users with preferences similar to the preferences of a current user are identified and information associated with the identified users is used to calculate a prediction for the current user. In A/B testing, users are randomly provided a control sample (option A) or a challenger sample (option B). User responses are evaluated to quantify the performance of the challenger sample over the control sample.